lrmest v3.0

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Different Types of Estimators to Deal with Multicollinearity

When multicollinearity exists among predictor variables of the linear model, least square estimators does not provide a better solution for estimating parameters. To deal with multicollinearity several estimators are proposed in the literature. Some of these estimators are Ordinary Least Square Estimator (OLSE), Ordinary Generalized Ordinary Least Square Estimator (OGOLSE), Ordinary Ridge Regression Estimator (ORRE), Ordinary Generalized Ridge Regression Estimator (OGRRE), Restricted Least Square Estimator (RLSE), Ordinary Generalized Restricted Least Square Estimator (OGRLSE), Ordinary Mixed Regression Estimator (OMRE), Ordinary Generalized Mixed Regression Estimator (OGMRE), Liu Estimator (LE), Ordinary Generalized Liu Estimator (OGLE), Restricted Liu Estimator (RLE), Ordinary Generalized Restricted Liu Estimator (OGRLE), Stochastic Restricted Liu Estimator (SRLE), Ordinary Generalized Stochastic Restricted Liu Estimator (OGSRLE), Type (1),(2),(3) Liu Estimator (Type-1,2,3 LTE), Ordinary Generalized Type (1),(2),(3) Liu Estimator (Type-1,2,3 OGLTE), Type (1),(2),(3) Adjusted Liu Estimator (Type-1,2,3 ALTE), Ordinary Generalized Type (1),(2),(3) Adjusted Liu Estimator (Type-1,2,3 OGALTE), Almost Unbiased Ridge Estimator (AURE), Ordinary Generalized Almost Unbiased Ridge Estimator (OGAURE), Almost Unbiased Liu Estimator (AULE), Ordinary Generalized Almost Unbiased Liu Estimator (OGAULE), Stochastic Restricted Ridge Estimator (SRRE), Ordinary Generalized Stochastic Restricted Ridge Estimator (OGSRRE), Restricted Ridge Regression Estimator (RRRE) and Ordinary Generalized Restricted Ridge Regression Estimator (OGRRRE). To select the best estimator in a practical situation the Mean Square Error (MSE) is used. Using this package scalar MSE value of all the above estimators and Prediction Sum of Square (PRESS) values of some of the estimators can be obtained, and the variation of the MSE and PRESS values for the relevant estimators can be shown graphically.

Functions in lrmest

Name Description
lrmest-package Estimation of varies types of estimators in the linear model
mixe Ordinary Mixed Regression Estimator
liu Liu Estimator
ogrls Ordinary Generalized Restricted Least Square Estimator
ogliu Ordinary Generalized Liu Estimator
ogrrre Ordinary Generalized Restricted Ridge Regression Estimator
lte3 Type (3) Liu Estimator
ogols Ordinary Generalized Ordinary Least Square Estimators
alte3 Type (3) Adjusted Liu Estimator
alte1 Type (1) Adjusted Liu Estimator
lte1 Type (1) Liu Estimator
ogalt1 Ordinary Generalized Type (1) Adjusted Liu Estimator
aul Almost Unbiased Liu Estimator
oglt1 Ordinary Generalized Type (1) Liu Estimator
checkm Check the degree of multicollinearity present in the dataset
srliu Stochastic Restricted Liu Estimator
ogaur Ordinary Generalized Almost Unbiased Ridge Estimator
ogre Ordinary Generalized Ridge Regression Estimator
rid Ordinary Ridge Regression Estimator
rrre Restricted Ridge Regression Estimator
alte2 Type (2) Adjusted Liu Estimator
aur Almost Unbiased Ridge Estimator
lte2 Type (2) Liu Estimator
ogaul Ordinary Generalized Almost Unbiased Liu Estimator
ogalt3 Ordinary Generalized Type (3) Adjusted Liu Estimator
ogrliu Ordinary Generalized Restricted Liu Estimator
optimum Summary of optimum scalar Mean Square Error values of all estimators and optimum Prediction Sum of Square values of some of the estimators
ogsrre Ordinary Generalized Stochastic Restricted Ridge Estimator
rliu Restricted Liu Estimator
ogalt2 Ordinary Generalized Type (2) Adjusted Liu Estimator
rls Restricted Least Square Estimator
pcd Portland Cement Dataset
ogsrliu Ordinary Generalized Stochastic Restricted Liu Estimator
ogmix Ordinary Generalized Mixed Regression Estimator
ols Ordinary Least Square Estimators
oglt2 Ordinary Generalized Type (2) Liu Estimator
oglt3 Ordinary Generalized Type (3) Liu Estimator
srre Stochastic Restricted Ridge Estimator
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Details

Type Package
Date 2016-05-13
LazyData yes
Repository CRAN
License GPL-2 | GPL-3
NeedsCompilation no
Packaged 2016-05-14 16:19:07 UTC; USER
Date/Publication 2016-05-14 23:22:37

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